Week # 06 "Capturing Tacit Knowledge"

Knowledge capture is a process by which the expert’s thoughts & experiences are captured. A knowledge developer collaborates with an expert to convert expertise into a coded program. Three important steps of knowledge capturing are:

• Use a suitable method to draw out information from the expert.
• Understand the information and conclude the expert’s knowledge and reasoning process.
• Use the interpretation to build rules that symbolize expert’s solutions.

One should improve the knowledge capture process by focusing on how experts come up to a problem. Look ahead of the facts or the heuristics. Re-evaluate how well the problem domain is understood and how precise the problem is replicated.

The qualifications of an expert include:

• Knowing when to follow ideas, and when to make exceptions.
• Intelligent to perceive the big image.
• Hold good communication skills.
• Can bear pressure.
• Capable to imagine artistically.

The advantages of using a single expert includes:

• Perfect when constructing a straightforward KM system.
• A crisis in a limited area.
• Easier to organize gatherings.
• Disagreements are easier to resolve.
• Shares more confidentiality than does multiple experts.

The disadvantages of using a single expert are:

• Sometimes expert’s knowledge is not easy to capture.
• Single expert provides only a single line of reasoning.
• Expert knowledge is sometimes dispersed.
• Single expert more likely to change scheduled meetings than experts in a team.

One can develop a relationship with experts by creating the right impression, understanding the expert’s style and deciding where to hold the session. Experts use analogies to explain events. Reliable knowledge capture requires understanding and interpreting expert’s verbal description of information. Interview is a tool that is used for evaluating the validity of information acquired. Various types of interviews are:

• Structured
• Semi-structured
• Unstructured

 A successful interview includes:

• Locate the stage and create understanding.
• Appropriately phrase the query.
• Queries building is essential.
• Pay attention closely and evade opinions.
• Assess meeting results.

The sources of errors that reduce Information Reliability:

• Expert’s perceptual view
• Expert’s failure to remember just what happened
• Expert’s fear of the unknown
• Communication problems

The problems encountered during the Interview:

• Response bias
• Inconsistency
• Communication difficulties
• Hostile attitude
• Standardized questions
• Lengthy questions
• Long interview

Week # 05 "Knowledge Creation & Knowledge Management Architecture"

Knowledge creation is a dynamic activity that can enhance the success and economic well-being of an organization. It involves knowledge acquisition, selection, generation & sharing. Knowledge creation and transfer is done by means of various teams. SECI model of knowledge evolution involves socialization, externalization, internalization & combination.

• Externalization: It is the process of codification. It has benefits in terms of efficiency & economics.
• Combination: It is the process of converting explicit knowledge from one form to another.
• Internalization: It is the individual cognitive processing of codified knowledge to generate context-specific, tacit knowledge.
• Socialization: It involves interacting with others in an informal sharing of ideas & expertise.

The key to knowledge creation lies in the way knowledge is being mobilized and converted through technology. The stages of KMSLC include:

• Evaluate existing infrastructure
• Form the KM team
• Knowledge capture
• Design KM blueprint
• Verify and validate the KM system
• Implement the KM system
• Management change & rewards structure
• Post-system evaluation

The layers of system are:

• User Interface
• Authorized access control
• Collaborative intelligence & filtering
• Knowledge-enabling applications
• Transport
• Middleware
• The Physical Layer
• Databases

These layers represent internal technologies of the company. The User Interface is the least technical, and data repository is the most technical layer.

• User Interface: The goal of this layer is to remove barriers to information and tacit (made explicit) knowledge represented in the data repositories. User interfaces should be consistent, relevant, visually clear, easy to navigate & easy to use.
• Authorized Access Control: Maintains security and ensures authorized access to the knowledge stored in company’s repositories
• Knowledge-enabling Applications: Provides knowledge bases, discussion databases, automation tools, etc. The goal is to demonstrate by knowledge sharing how employees’ performances are improved.
• Transport Layer: Includes LANs, WANs, intranets, extranets & the Internet. Ensures that the company will become a network of relationships.
• Middleware: Focus on interfacing with legacy systems and programs residing on other platforms. Makes it possible to connect between old and new data formats.
• Physical Repositories: Represents the physical layer where repositories are installed. Includes data warehouses, legacy applications, operational databases, and special applications for security and traffic management.

Week # 04 "KM Life Cycle"

Various of diverse methods have been planned for KMSLC. The predictable approaches can still be used for mounting KM system and often substituted by iterative design and prototyping. Knowledge Management systems are developed in order to fulfill the need for improving efficiency and potential of employees and the company as a whole. The offered knowledge infrastructure gives the insight that the current ways of doing things are not unmanageable in first choice for a new system.

We can check the feasibility of a project by addressing its affordability, whether it is appropriate and its cost. The tasks involved in conducting a feasibility study include:

• Forming a knowledge management team.
• Preparing a Master Plan.
• Performing cost/benefit analysis of the system.
• Quantifying system criteria and costs.

The user support is also an important aspect which is to be considered during the Km system development. The main points which must be considered includes:

• How the system is perceived by the user?
• How many involvements can be expected from the user during system development?
• What type of user training will be needed?
• What kind of operational support should be provided?

During the strategic planning of the system the areas to be considered are: Vision, Resources and Culture. While forming a KM Team one should Identify the key units, branches, divisions etc, Strategically, technically and organizationally balancing the team size and competency.

Factors that impact the team success are:

• Quality, capability and size of team
• Complexity of the project
• Team motivation and leadership

Capturing Knowledge involves extracting, analyzing and interpreting the concerned knowledge that a human expert uses to solve a specific problem. Interviewing is the most popular methods used to capture knowledge. Data mining is also a very useful method used for Knowledge capturing. 

Knowledge capture and knowledge transfer are often carried out through teams. Usually Knowledge developers use iterative approach for capturing knowledge. The spontaneous and iterative process of building a knowledge base is referred to as rapid programming.

A knowledge developer can be considered as the architect of the system. In the blueprint designing phase the Knowledge Management infrastructure’s design is initiated. The Key layers of KM Architecture are:

• User Interface
• Security Layer
• Collaborative agents and filtering
• Application layer
• Transport internet layer
• Physical Layer
• Sources

The testing phase involve two steps: Verification Procedure, Validation Procedure. In the Implementation phase the new KM system is rehabilitated into real operation. Conversion is the major step in case of implementation. Quality Assurance point to the development of controls to ensure a quality KM system.

The user training depends on the user’s knowledge level and the system’s attributes. Training should be geared to the exact user based on ability, experience and system complexity. 

Training can be carried by user manuals, explanatory facilities and job aids.

Implementation refers to change, and organizational members usually oppose modify. Resistance can be observed in the form of Projection, Avoidance and Aggression. 

Week # 03 "Knowledge Management System Life Cycle"

The challenges that are faced building a knowledge management system are:

·         Changing Organization Culture

·         Knowledge Evaluation

·         Knowledge Processing

·         Knowledge Implementation

The differences between Conventional System Life Cycle (CSLC) Versus Knowledge Management System Life Cycle (KMSLC) are as follows:

Conventional System Life Cycle (CSLC)	Knowledge Management System Life Cycle (KMSLC)
It is primarily sequential.	Is incremental and interactive.
It is process driven or specifies then builds.	It is result oriented or start slow and grow.
The System testing normally at the end in CSLC.	KM system testing evolves from beginning of the cycle.

The similarities of CSLC & KMSLC are:

• They both begin with a problem and end with a solution
• They both begin with information gathering or knowledge capture
• Testing is essentially the same to make sure “the system is right” and “it is the right system”
• Both developers must choose the appropriate tool(s) for designing their respective systems

Stages of KMSLC

1. Evaluate Existing Infrastructure
2. Form the KM Team
3. Knowledge Capture
4. Design KM Blueprint
5. Verify and validate the KM System
6. Implement the KM System
7. Manage Change and Rewards Structure
8. Post System Evaluation

Stage 1- Evaluate Existing Infrastructure

The project boundary lies within financial, human resource, and operational constraints. In order to predict the benefits of the user, the project must be completed rapidly.

Knowledge developer should consider:

• Vision
• Resources
• Culture

Stage 2- Form the KM Team

Identify the key stakeholders of the prospective KM system. 

Stage 3 - Knowledge Capture

• EXPLICIT KNOWLEDGE: It is captured in repositories from various media
• TACIT KNOWLEDGE: It is captured from company experts using various tools and methodologies

Stage 4 - Design KM Blueprint

The blueprint is the physical design.

               

Stage 5 - Verify and validate the KM System

• Verification: The system has the right functions
• Validation: The system has the right output

Stage 6 - Implement the KM System          

• KM system is converted into a new actual operation
• The files or data are converted
• User training is included
• Quality assurance is essential

Stage 7 - Manage Change and Rewards Structure

Goal is to minimize resistance to change

• Experts
• Regular employees (users)
• Troublemakers

Stage 8 - Post-system evaluation

Assess system impact in terms of effects on:

• People
• Procedures
• Performance of the business

Areas of concern

• Quality of decision making
• Attitude of end users
• Costs of Knowledge processing and update

Week # 02 "Understanding Knowledge"

Some important definitions covered in the chapter are:

• Fact: A statement that represents truth.
• Procedural Rule: A rule that specifies the sequence of actions.
• Heuristic: A rule of thumb based on experience.
• Intelligence: The capability to obtain and relate appropriate knowledge.
• Memory: The ability to store and retrieve relevant experience.
• Learning: The skill of acquiring knowledge using the method of study.
• Experience: The understanding that is developed through past actions.
• Common Sense: The natural and usually unreflective opinions of humans.
• Declarative Knowledge: Centers on ideas about dealings among variables.
• Procedural Knowledge: Centers the ideas relating to sequences of steps or actions to desired (or undesired) results.
• Tacit Knowledge: Includes visions, perceptions and guesses.
• Explicit Knowledge: Knowledge that has been expressed into words and numbers.
• Externalization: Process of articulating tacit knowledge into explicit concepts.
• Metaphor: A figure of speech that uses one thing to mean another.
• Analogy: Shows similarity among things that may seem different.
• Knowledge Conversion: Tacit and explicit knowledge interact and interchange into each other.
• Deductive Reasoning: Comprises of exact facts and conclusions.
• Inductive Reasoning: Reasoning from a set of facts or individual cases.

Cognitive Psychology is the interdisciplinary study of Human Intelligence. Its two major components are: Experimental Psychology & Artificial Intelligence. Data comprises facts, observations or perceptions whereas, Information is processed data. It involves manipulated data. Knowledge is a justified true belief. Knowledge helps to produce information from data or from less valuable information to more valuable information. Data or information can modify knowledge.

The subjective view of Knowledge is that it can be viewed as an ongoing accomplishment which continuously affects and is influenced by social practices. Its 2 perspectives are:

• Knowledge as state of Individual Mind.
• Knowledge as practice.          

Whereas its objective view is that it can be located in the form of an object or a capability that can be discovered. Its 3 perspectives are:

• Knowledge as objects.
• Knowledge as access to information.
• Knowledge as capability. 

The common types of knowledge are:

• Simple Knowledge
• Complex Knowledge
• Support Knowledge
• Tactical Knowledge
• Strategic Knowledge

An Expertise is the knowledge of higher quality. The types of expertise are:

• Association Expertise
• Motor Skills Expertise
• Theoretical Expertise

The expert reasoning methods includes:

• Reasoning by analogy
• Formal reasoning
• Case-based reasoning

Human Memory never runs out of space. Types of human learning are:

• Learning by experience
• Learning by example
• Learning by discovery

Week # 01 "Introduction to Knowledge Based Management System"

The chapter mainly comprises of the following basic definitions related to KBMS.

Data: Raw facts and figures.

Information: Data which has some meaning associated with it.

Knowledge: Understanding of the information which has been given.

Knowledge Management: Doing what is needed to get the most out of knowledge resources.

Processes necessary to generate, capture, organize, and transfer knowledge across the organization to achieve competitive advantage.

The forces motivating Knowledge Management are:

• Increasing Domain complexity
• Accelerating market Volatility.
• Intensified speed of Responsiveness
• Diminishing individual Experience

Information technology facilitates sharing as well as accelerated growth of knowledge and also allows the movement of information at increasing speed and efficiency. Knowledge management mechanisms are organizational or structural means used to promote knowledge management. Knowledge Management System is the interaction between latest technologies and social/structural mechanisms. The classifications of KM are:

• Knowledge Discovery System
• Knowledge Capture System
• Knowledge Sharing System